1. Field
Methods and apparatuses consistent with exemplary embodiments of the present inventive concept relate to adaptive image processing in an image pyramid, and more particularly, to an adaptive image processing apparatus and method which sparsely extracts samples according to scale levels of an image pyramid from the image pyramid in which a plurality of images having different scale levels are aligned according to scale levels, searches for a suitable scale level around a scale level selected from the extracted samples, and performs image processing on the suitable scale level.
2. Description of the Related Art
A technology of extracting a feature point from an image, for example, an image obtained by a camera, is widely used in a computer vision field including personal authentication, three-dimensional (3D) reconstruction, and tracking. Representative examples of an algorithm for extracting a feature point from an image include a scale-invariant feature transform (SIFT) algorithm and a speeded up robust feature (SURF) algorithm which may detect an object in a scale-invariant manner. For such scale-invariant characteristics, an image pyramid technique may be used.
An image pyramid technique involves converting a model to be matched and an input image into images having various scales and performing an operation according to algorithms for extracting a feature point or performing other image processing. For example, when an SIFT algorithm that is a representative algorithm for extracting a feature point in a scale-invariant manner is used, an image pyramid technique may pass a filtered image through a Gaussian filter having variances of various scales to obtain resultant images, sequentially smooth the resultant images according to adjacent scales to derive a Gaussian smoothed image, subsample the Gaussian smoothed image by a factor of two (2) to obtain resultant images, repeatedly pass the resultant images through the Gaussian filter having the variances of various scales to form an image pyramid composed of Gaussian smoothed images, and perform a series of operations for image processing on the image pyramid.
Such an image pyramid technique has a disadvantage in that an operation time is too long. This is because after an input image is resized to obtain images having various scale levels, a feature point is detected from an entire area of each image or other image processing needs to be repeatedly performed. Since a feature point is detected and operations for image processing are repeatedly performed on images having various scale levels, an operation time is increased and a false positive rate is increased.